5 Brutal Truths Every CEO Wishes Data Scientists Understood.

Because while you’re tuning hyperparameters, your CEO is tuning investor expectations.

Author

Glenda Carnate
November 06, 2025

Read time: 2.5 minutes

Every dashboard tells a story, but not every story leads to a decision. After working in both building models and managing P&Ls, one thing is clear: data science is not the hardest part. The real challenge is translating insights.

Once, our model reached 96% accuracy and the team celebrated. But the next week, when I asked myself, “So… what changed in the business?” there was only silence.

That’s when I realized executives don’t focus on precision; they care about progress. Until your work makes a difference in what matters to them, you are just speaking in code.

According to recent research, a McKinsey 2025 report found that while many organizations have adopted AI, only 39% report any EBIT impact, and for most, AI contributes less than 5% of total profits.

This highlights a critical reality: AI models alone don’t create value unless they’re tied directly to business strategy and decision-making.

Reality Check: 5 Brutal Truths Every Data Scientist Needs to Hear.

1. More data ≠ more truth.
Collecting everything doesn’t make you smarter, but it can definitely make you slower. True insight comes from clarity, not quantity. Focus on the variables that move real decisions, and let the rest go.

2. High accuracy doesn’t mean high impact.
A 97% accurate model means nothing if it doesn’t change behavior. The best data science isn’t about prediction, it’s about provoking action.

3. Bias leaks into everything.
Every dataset carries the fingerprints of its origin. Ignore bias, and you’ll end up scaling the wrong assumptions. Guard your models like policies, with regular checks, re-sampling, and human judgment.

4. Insights expire fast.
An unshared insight is just wasted potential. In fast-moving markets, speed beats precision. Act while the window’s open because perfection can wait.

5. Executives don’t buy models, they buy movement.
At the end of the day, the only language that matters is results: risk down, margin up, churn lower.
If your insights can’t be measured in business outcomes, they’re still just experiments, not impact.

💡Key Takeaway: 

Be the person who turns numbers into momentum, not just models into meetings. Because the most powerful algorithm in business is still clarity + action.

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👉 COMMENT: What’s the one brutal truth you think most data teams still ignore?

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